Clinical research data management and analytics
Life science organizations are facing a crisis in cost effectively uncovering drug targets. In many cases, these challenges stem from issues with data and technology rather than the research itself. For example, researchers within R&D organizations are grappling with data explosion at a rate of 48% annually1 — while still working on siloed infrastructures and legacy systems.
With the help of Google Cloud's R&D data management and analysis solution, researchers can expedite their drug discovery and research through modernized infrastructure, effective data management, and efficient collaboration. Life science organizations benefit from our solution that's comprised of products specifically built for them, including: Healthcare API for Clinical Data (HL7v2, FHIR) and Medical Imaging (DICOM), and G Suite (supporting HIPAA compliance). Through this comprehensive R&D solution, life science organizations can manage large volumes of structured and unstructured data siloed across research sites as well as quickly analyze and generate insights from large amounts of data using Google Cloud's fully managed data warehouse BigQuery and Google Cloud's fully managed TensorFlow service Cloud ML Engine.
Cross-sector data integration
Researchers process and analyze data from multiple sources including genomics, imaging, and real-world data. To support this, life science organizations must be able to analyze huge amounts of data across disparate platforms. For example, biomedical data research requires that organizations structure, join, and query many different types of biomedical data and analyze each base pair upwards of 30 times for sequencing.
The Google Cloud data integration solution set consists of solutions that integrate different types of data used within life science R&D with products built specifically for healthcare and life science organizations. Our genomics solution, built on top of our Analytics Suite, provides a platform for researchers to structure, join, and query biomedical data while making sharing easier and more flexible for both public datasets and controlled access datasets. The solution to analyze images is built on the Healthcare API which stores DICOM objects. This enables analysis of healthcare images at scale to accelerate preclinical research and contextualize medical imaging data with other emerging datasets across modalities (such as genomics). Finally, our R&D data integration solution gives researchers the ability to unite public data and other datasets hosted on the cloud. By building a clinical data warehouse on GCP and incorporating the Healthcare API, life sciences organizations can enable more rapid research and learning.
Virtual clinical trial
Clinical trials are costly, time consuming, and prone to recruitment issues, often stemming from ineffective analysis, manual data entry, legacy systems, and other data challenges. These inefficiencies can have grave repercussions, including preventing patients from receiving life-saving treatments and as much as $8M in lost revenue for each day a drug is delayed.2
The Google Cloud virtual clinical trial solution revolutionizes data collection, storage, and analysis to bring effective and approved treatments to patients faster. Through these solutions, life science organizations can manage large volumes of structured and unstructured data siloed across clinical trial sites. By building a clinical data warehouse on GCP paired with analytics products, and tools like BigQuery and Cloud ML Engine, organizations can gain insights into their clinical data faster. Finally, to enable clinical trials collaboration, our HIPAA enabled G Suite solution helps life science organizations enhance productivity to get both protocols and submissions developed and reviewed more quickly — all while keeping proprietary and sensitive data secure and anonymous.
Improve data analysis with smarter storage
Siloed and fragmented data hinders scientific research and delays the drug development process. Storing your organization's data in a way that is useful for analytics is the first step in enabling insights. With Google Cloud big data solutions, you can aggregate, store, and de-identify your data. Then connect your data to advanced Google Cloud capabilities with the Cloud Healthcare API.
Make sense of your biomedical data
The life sciences community requires large amounts of data to be analyzed quickly and effectively, delivering insights from diverse datasets, including clinical, R&D, and customer/patient data. With BigQuery, our fully managed serverless data warehouse, you can quickly find meaningful insights without having to manage infrastructure.
For biomedical data, Variant Transforms leverages BigQuery to apply data science on genomic variants alongside other datasets. Our Genomics tools are based on years of Google innovation and can process petabytes of data (even in parallel) faster than can be done on-premises.
Improve the drug development process
Help accelerate the pharmaceutical development process by identifying promising drug discoveries based on predictive analytics. Using Cloud ML Engine and TensorFlow, you could build and train custom models to automatically detect patterns in your pre-clinical research, clinical trials, and post-market surveillance data. Then build upon this to help personalize patient treatments and create unique patient-specific treatment.
Empower compliant and cross-functional collaboration
Today's life science organizations employ dispersed, global workforces that need to collaborate in real time. From G Suite cloud-based productivity tools, to Chromebooks that won't fail while capturing clinical trial data, Google Cloud solutions make healthcare collaboration simple. Platforms that support HIPAA compliance enable patient and trial participant data to be captured remotely and securely. Furthermore, increase productivity by enabling users to easily search and find information they need across all content repositories with Cloud Search.
Build new technology that helps your patients, customers, and organization
As patient expectations for seamless care increase, interoperability of data sources is crucial. Cloud Healthcare API links care systems and applications built on Google Cloud, simplifying application development and device integration while supporting HL7v2, FHIR, and DICOM standards. The result? A more synchronized patient experience that also drives drug adherence.
Securing your most at-risk data
Pharma is among the top three sectors targeted by hackers.1 We do our part to help you protect your data across your organization by offering comprehensive identity management, network security, and threat detection and response capabilities to protect your organization against current and future threats. To earn your trust, we certify Google Cloud Platform and G Suite against the most rigorous global security and privacy standards like ISO 27001, ISO 27017, and ISO 27018, and make certain products available under applicable HIPAA business associate agreements. In addition, Google Cloud supports HIPAA compliance and is HITRUST CSF certified.
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Highlights from Next ’19
Catch up on the latest updates from Next ’19. See how life sciences organizations solve data problems with Google Cloud.
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